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Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II

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A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D：Materials and Processing".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 19466

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Dr. Davide Masato

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Department of Plastics Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA
Interests: polymer processing; product design; modeling and simulation; micro manufacturing; recycling
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Prof. Giovanni Lucchetta

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Guest Editor

Department of Industrial Engineering, University of Padova, Via Venezia 1, 35131 Padova, Italy
Interests: polymer processing; injection molding; fiber-reinforced plastic; polymers
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Special Issue Information

Dear Colleagues,

Micro and nano manufacturing technologies have been developed in research and industrial environment with the goal of supporting product miniaturization and integration of new functionalities. The technological development of new materials and processing methods needs to be supported by predictive models, which can simulate the interactions between materials, process states, and product properties. In comparison with the conventional manufacturing scale, micro and nano scale technologies require the study of different mechanical, thermal, and fluid dynamics, phenomena that need to be studied and modeled.

This Special Issue is dedicated to advances in the modeling of micro and nano manufacturing processes (micro/nano injection molding, powder injection molding, micro milling, micro EDM, micro water-jet, additive manufacturing, etc.). Invited and submitted articles should investigate the development of new models, validation of state-of-the-art modeling strategies, and approaches to material model calibration. Authors are encouraged to compare theoretical predictions to experimental observations, and examine the effect of different processing factors on selected process response variables. This Special Issue is not limited with respect to the type of material and manufacturing method. The goal is to provide state-of-the-art examples of the use of modeling and simulation in micro and nano manufacturing processes, promoting the diffusion and development of these technologies.

We look forward to receiving your contributions!

Prof. Davide Masato
Prof. Giovanni Lucchetta
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Micro manufacturing
Modeling
Simulation
Materials
Processing

Related Special Issues

Advances in Micro and Nano Manufacturing: Process Modeling and Applications in Micromachines (13 articles)
Advances in Micro and Nano Manufacturing: Process Modeling and Applications, 3rd Edition in Micromachines (2 articles)

Published Papers (10 papers)

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Research

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30 pages, 22197 KiB

Open AccessArticle

Dynamic Modeling for Chatter Analysis in Micro-Milling by Integrating Effects of Centrifugal Force, Gyroscopic Moment, and Tool Runout

by Xiaoli Liu, Dexuan Liu, Canyang Du, Yang Li, Caidong Wang and Zhijun Fu

Micromachines 2024, 15(2), 244; https://0-doi-org.brum.beds.ac.uk/10.3390/mi15020244 - 06 Feb 2024

Viewed by 618

Abstract

During micro-milling, regenerative chatter will decrease the machining accuracy, destabilize the micro-milling process, shorten the life of the micro-mill, and increase machining failures. Establishing a mathematical model of chatter vibration is essential to suppressing the adverse impact of chatter. The mathematical model must include the dynamic motions of the cutting system with the spindle–holder–tool assembly and tool runout. In this study, an integrated model was developed by considering the centrifugal force induced by rotational speeds, the gyroscopic effect introduced by high speeds, and the tool runout caused by uncertain factors. The tool-tip frequency-response functions (FRFs) obtained by theoretical calculations and the results predicted by simulation experiments were compared to verify the developed model. And stability lobe diagrams (SLDs) and time-domain responses are depicted and analyzed. Furthermore, experiments on tool-tip FRFs and micro-milling were conducted. The results validate the effectiveness of the integrated model, which can calculate the tool-tip FRFs, SLDs, and time responses to analyze chatter stability by considering the centrifugal force, gyroscopic effect, and tool runout. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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18 pages, 16337 KiB

Open AccessArticle

Wetting Characteristics of Laser-Ablated Hierarchical Textures Replicated by Micro Injection Molding

by Peng Gao, Ian MacKay, Andrea Gruber, Joshua Krantz, Leonardo Piccolo, Giovanni Lucchetta, Riccardo Pelaccia, Leonardo Orazi and Davide Masato

Micromachines 2023, 14(4), 863; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14040863 - 16 Apr 2023

Cited by 2 | Viewed by 1567

Abstract

Texturing can be used to functionalize the surface of plastic parts and, in particular, to modify the interaction with fluids. Wetting functionalization can be used for microfluidics, medical devices, scaffolds, and more. In this research, hierarchical textures were generated on steel mold inserts using femtosecond laser ablation to transfer on plastic parts surface via injection molding. Different textures were designed to study the effects of various hierarchical geometries on the wetting behavior. The textures are designed to create wetting functionalization while avoiding high aspect ratio features, which are complex to replicate and difficult to manufacture at scale. Nano-scale ripples were generated over the micro-scale texture by creating laser-induced periodic surface structures. The textured molds were then replicated by micro-injection molding using polypropylene and poly(methyl methacrylate). The static wetting behavior was investigated on steel inserts and molded parts and compared to the theoretical values obtained from the Cassie–Baxter and Wenzel models. The experimental results showed correlations between texture design, injection molding replication, and wetting properties. The wetting behavior on the polypropylene parts followed the Cassie–Baxter model, while for PMMA, a composite wetting state of Cassie–Baxter and Wenzel was observed. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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13 pages, 2501 KiB

Open AccessArticle

Prediction of Both E-Jet Printing Ejection Cycle Time and Droplet Diameter Based on Random Forest Regression

by Yuanfen Chen, Zongkun Lao, Renzhi Wang, Jinwei Li, Jingyao Gai and Hui You

Micromachines 2023, 14(3), 623; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14030623 - 08 Mar 2023

Cited by 1 | Viewed by 1222

Abstract

Electrohydrodynamic jet (E-jet) printing has broad application prospects in the preparation of flexible electronics and optical devices. Ejection cycle time and droplet size are two key factors affecting E-jet-printing quality, but due to the complex process of E-jet printing, it remains a challenge to establish accurate relationships among ejection cycle time and droplet diameter and printing parameters. This paper develops a model based on random forest regression (RFR) for E-jet-printing prediction. Trained with 72 groups of experimental data obtained under four printing parameters (voltage, nozzle-to-substrate distance, liquid viscosity, and liquid conductivity), the RFR model achieved a MAPE (mean absolute percent error) of 4.35% and an RMSE (root mean square error) of 0.04 ms for eject cycle prediction, as well as a MAPE of 2.89% and an RMSE of 0.96 μm for droplet diameter prediction. With limited training data, the RFR model achieved the best prediction accuracy among several machine-learning models (RFR, CART, SVR, and ANN). The proposed prediction model provides an efficient and effective way to simultaneously predict the ejection cycle time and droplet diameter, advancing E-jet printing toward the goal of accurate, drop-on-demand printing. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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17 pages, 9193 KiB

Open AccessArticle

Three-Dimensional Pulse-Based Modelling of Femtosecond Laser Ablation of Metals: Validation with Grooves

by Pol Vanwersch, Balasubramanian Nagarajan, Albert Van Bael and Sylvie Castagne

Micromachines 2023, 14(3), 593; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14030593 - 01 Mar 2023

Cited by 1 | Viewed by 1653

Abstract

The femtosecond (fs) laser ablation of metals is a precise method used to create microfeatures on the surface of the material with a minimized heat-affected zone (HAZ). Despite its many advantages, fs laser ablation often requires extensive trial-and-error experimentation before finding the optimal laser strategy for a desired geometry with minimal HAZ. The pulse-based two-temperature model (TTM) can significantly shorten this process by predicting the ablated geometry based on a set of material and laser parameters. However, this model has only been validated for percussion drilling and single lines. In this study, the pulse-based TTM is tested against parallel line experiments and subsequently modified to include geometry-dependent material parameters. More specifically, the threshold fluence and reflectivity of the material are modified to incorporate the temperature increase inside the standing features between parallel lines. The introduced geometry-dependent factors are fitted with experimental data and their inclusion in the model is shown to have a positive impact on the simulation results. The results show a clear amelioration in the shape and depth of the simulated profiles, with the error on the average depth and width of the modified TTM being lower than the average standard deviation on the experiments. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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10 pages, 3223 KiB

Open AccessArticle

Experimental Study on the Grinding of an Fe-Cr-Co Permanent Magnet Alloy under a Small Cutting Depth

by Ningchang Wang, Feng Jiang, Jianhui Zhu, Yuchun Xu, Chaoyu Shi, Heliang Yan and Chunqing Gu

Micromachines 2022, 13(9), 1403; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091403 - 26 Aug 2022

Cited by 1 | Viewed by 938

Abstract

A small cutting depth is the key parameter to realize precision in the machining process. The stability of the machining process will directly affect the quality of machining. In this study, dry grinding experiments using an Fe-Cr-Co permanent magnet alloy with small cutting depths (5 μm) were carried out. The relationship between the number of peaks and valleys and the quality control of the grinding force, wheel speed and feed speed were analyzed. The relationship between the peak and valley values of the grinding force signals and the peak and valley values of the grinding surface obtained using a white light interferometer was revealed. The influence of the grinding parameters on the grinding forces was analyzed by processing the grinding force signals with a low-pass filter based on the rotational speed of the grinding wheel. The experimental results indicated that the difference in grinding force between the peak and valley could be reduced by increasing the grinding wheel speed, which was mainly due to a decrease in average grinding force when the maximum undeformed cutting thickness of the single abrasive decreased. The actual height difference between the grinding surface peak and valley could be realized by increasing the grinding wheel speed. The feed speed of the worktable had no effect on the grinding force signal and the peaks and valleys of the surface morphology. Lower surface roughness could be achieved by reducing the feed speed and increasing the grinding wheel speed. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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11 pages, 4748 KiB

Open AccessArticle

Identification of Preisach Model Parameters Based on an Improved Particle Swarm Optimization Method for Piezoelectric Actuators in Micro-Manufacturing Stages

by Lei Yang, Bingxiao Ding, Wenhu Liao and Yangmin Li

Micromachines 2022, 13(5), 698; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13050698 - 29 Apr 2022

Cited by 14 | Viewed by 1998

Abstract

The Preisach model is a typical scalar mathematical model used to describe the hysteresis phenomena, and it attracts considerable attention. However, parameter identification for the Preisach model remains a challenging issue. In this paper, an improved particle swarm optimization (IPSO) method is proposed to identify Preisach model parameters. Firstly, the Preisach model is established by introducing a Gaussian−Gaussian distribution function to replace density function. Secondly, the IPSO algorithm is adopted to Fimplement the parameter identification. Finally, the model parameter identification results are compared with the hysteresis loop of the piezoelectric actuator. Compared with the traditional Particle Swarm Optimization (PSO) algorithm, the IPSO algorithm demonstrates faster convergence, less calculation time and higher calculation accuracy. This proposed method provides an efficient approach to model and identify the Preisach hysteresis of piezoelectric actuators. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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14 pages, 4977 KiB

Open AccessArticle

Fused Deposition Modeling of Microfluidic Chips in Transparent Polystyrene

by Markus Mader, Christof Rein, Eveline Konrat, Sophia Lena Meermeyer, Cornelia Lee-Thedieck, Frederik Kotz-Helmer and Bastian E. Rapp

Micromachines 2021, 12(11), 1348; https://0-doi-org.brum.beds.ac.uk/10.3390/mi12111348 - 31 Oct 2021

Cited by 14 | Viewed by 2762

Abstract

Polystyrene (PS) is one of the most commonly used thermoplastic materials worldwide and plays a ubiquitous role in today’s biomedical and life science industry and research. The main advantage of PS lies in its facile processability, its excellent optical and mechanical properties, as well as its biocompatibility. However, PS is only rarely used in microfluidic prototyping, since the structuring of PS is mainly performed using industrial-scale replication processes. So far, microfluidic chips in PS have not been accessible to rapid prototyping via 3D printing. In this work, we present, for the first time, 3D printing of transparent PS using fused deposition modeling (FDM). We present FDM printing of transparent PS microfluidic channels with dimensions as small as 300 µm and a high transparency in the region of interest. Furthermore, we demonstrate the fabrication of functional chips such as Tesla-mixer and mixer cascades. Cell culture experiments showed a high cell viability during seven days of culturing, as well as enabling cell adhesion and proliferation. With the aid of this new PS prototyping method, the development of future biomedical microfluidic chips will be significantly accelerated, as it enables using PS from the early academic prototyping all the way to industrial-scale mass replication. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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18 pages, 8738 KiB

Open AccessArticle

Analyzing the Effect of Particle Shape on Deformation Mechanism during Cutting Simulation of SiC P/Al Composites

by Jiakang Zhou, Jieqiong Lin, Mingming Lu, Xian Jing, Yubo Jin and Dunlan Song

Micromachines 2021, 12(8), 953; https://0-doi-org.brum.beds.ac.uk/10.3390/mi12080953 - 12 Aug 2021

Cited by 7 | Viewed by 1998

Abstract

To analyze the effect of particle shape on deformational behavior in the cutting simulation process for metal matrix composites (MMCs), two 2D mesoscopic-based finite element (FE) models reinforced with randomly distributed circular and irregular polygonal particles were developed. Different material properties (metal matrix phase, particle reinforced phase) and the properties of the particle–matrix interface were comprehensively considered in the proposed FE model. Systematic cutting experiments were conducted to compare the differences between two modeling approaches with respect to particle fracture, chip formation, cutting force and surface integrity. The results show that the irregular polygonal particle model is closer to the microstructure of MMCs, and is better able to reflect the deformation behavior of particles. The simulation model with irregular polygonal particles is even able to capture more details of the impact caused by particles, reflecting variations in the cutting force in the actual cutting process. The initiation and propagation of microcracks is mainly determined on the basis of particle geometry and further affects chip formation. Both models are able to correctly reflect surface defects, but the irregular polygonal particle model provides a more comprehensive prediction for the subsurface damage of MMCs. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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12 pages, 2573 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Comparison between Finite Element Model (FEM) Simulation and an Integrated Artificial Neural Network (ANN)-Particle Swarm Optimization (PSO) Approach to Forecast Performances of Micro Electro Discharge Machining (Micro-EDM) Drilling

by Mariangela Quarto, Gianluca D’Urso, Claudio Giardini, Giancarlo Maccarini and Mattia Carminati

Micromachines 2021, 12(6), 667; https://0-doi-org.brum.beds.ac.uk/10.3390/mi12060667 - 07 Jun 2021

Cited by 25 | Viewed by 4329

Abstract

Artificial Neural Network (ANN), together with a Particle Swarm Optimization (PSO) and Finite Element Model (FEM), was used to forecast the process performances for the Micro Electrical Discharge Machining (micro-EDM) drilling process. The integrated ANN-PSO methodology has a double direction functionality, responding to different industrial needs. It allows to optimize the process parameters as a function of the required performances and, at the same time, it allows to forecast the process performances fixing the process parameters. The functionality is strictly related to the input and/or output fixed in the model. The FEM model was based on the capacity of modeling the removal process through the mesh element deletion, simulating electrical discharges through a proper heat-flux. This paper compares these prevision models, relating the expected results with the experimental data. In general, the results show that the integrated ANN-PSO methodology is more accurate in the performance previsions. Furthermore, the ANN-PSO model is faster and easier to apply, but it requires a large amount of historical data for the ANN training. On the contrary, the FEM is more complex to set up, since many physical and thermal characteristics of the materials are necessary, and a great deal of time is required for a single simulation. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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13 pages, 5467 KiB

Open AccessBrief Report

Numerical Simulation of Deformation in Hot Runner Manifold

by Jae Sung Jung and Sun Kyoung Kim

Micromachines 2023, 14(7), 1337; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14071337 - 29 Jun 2023

Viewed by 1016

Abstract

This study simulated the deformation of a hot runner manifold and nozzle assembly during operation, aiming to address potential leaks and premature failure. Both thermal and mechanical models were used simultaneously to accurately capture system behavior. A simplified set of boundary conditions was proposed for efficient problem-solving. Analysis of the simulation results revealed that thermal deformation posed a risk of catastrophic failures and leaks. Deformation from melt pressure was relatively small compared to thermal loading, not exceeding 12%. The study provided design recommendations based on the simulation findings, guiding the development of hot runner systems for improved reliability. Full article

(This article belongs to the Special Issue Advances in Micro and Nano Manufacturing: Process Modeling and Applications, Volume II)

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